中国空间科学技术 ›› 2022, Vol. 42 ›› Issue (4): 45-53.doi: 10.16708/j.cnki.1000-758X.2022.0051

• 论文 • 上一篇    下一篇

快收敛高可靠PPP-RTK大气改正模型生成方法

田野,张立新*,边朗   

  1. 中国空间技术研究院西安分院,西安710000
  • 出版日期:2022-08-25 发布日期:2022-08-09

A PPP-RTK atmospheric correction model generation method with fast convergence and high reliability

TIAN Ye,ZHANG Lixin*,BIAN Lang   

  1. China Academy of Space Technology Xi′an,Xi′an 710000,China
  • Published:2022-08-25 Online:2022-08-09

摘要: 生成快收敛、高可靠的大气改正模型是PPP-RTK(precise point positioning-real-time kinematic)应用的关键和瓶颈问题。对顾及快收敛和可靠性的PPP-RTK大气改正模型生成方法进行了研究,通过迭代约束和时域约束保证其快收敛与可靠性,利用武汉CORS(continuously operating reference stations,连续运行参考站)进行试验,45s能够实现水平10cm(95%)的定位精度。在此基础上利用香港CORS进一步验证与分析得出:增加格网密度能够提升定位精度但会增加信息量,需要综合考虑定位效果和播发的信息量,面向普通用户的格网大小经纬度建议设置为0.5°~0.8°;生成大气改正模型的参考站空间分布必须合理且均匀,同时提出可以在合理范围内加入虚拟参考站约束大气改正模型的生成从而保证其收敛性与可靠性。

关键词: 快收敛, 高可靠, PPP-RTK, 大气改正模型, 虚拟参考站

Abstract: The key and bottleneck of PPP-RTK application is the generation of atmospheric correction model with fast convergence and high reliability.The PPP-RTK atmospheric correction model generation method mentioned above was investigated.The fast convergence and reliability were ensured by iterative constraints and time domain constraints,and the horizontal 10cm(95%)positioning accuracy was achieved in 45s using Wuhan CORS.On this basis,Hong Kong CORS was used for further validation and analysis.Although increasing the grid density can improve the positioning accuracy,the amount of information is increased.It is necessary to consider the positioning effect and the amount of broadcasted information,and the latitude and longitude of grid size for general users are suggested to be set at 0.5°~0.8°.The spatial distribution of reference stations must be reasonable and uniform,and it was proposed that virtual reference stations can be added within a reasonable range to constrain the generation of atmospheric correction models,thus ensuring their convergence and reliability.

Key words: fast convergence, high reliability, PPP-RTK, atmospheric correction model, virtual reference station